class_docstr: Testing suite for Bark - tests all the tests defined in `BetterTransformersTestMixin`
  Since `Bark` is a text-to-speech model, it is preferrable
  to define its own testing class.
code: def test_generation(
      self, test_name: str, model_type: str, batch_size: int
  ):
      model_id = MODELS_DICT[model_type]
      processor = AutoProcessor.from_pretrained(model_id)
  
      model = AutoModel.from_pretrained(model_id)
  
      text = ["This is me and me"]
      if batch_size > 1:
          text.append("Please continue this my dear me")
      inp = processor(text, return_tensors="pt")
  
      length = 50
  
      result_vanilla = model.generate(
          **inp,
          num_beams=1,
          fine_temperature=None,
          do_sample=False,
          semantic_max_new_tokens=length,
      )
  
      model = BetterTransformer.transform(model)
  
      result_bettertransformer = model.generate(
          **inp,
          num_beams=1,
          fine_temperature=None,
          do_sample=False,
          semantic_max_new_tokens=length,
      )
  
      self.assertTrue(
          torch.allclose(result_vanilla, result_bettertransformer),
          f" Maxdiff: {(result_vanilla - result_bettertransformer).abs().max()}",
      )
  
imports: import unittest
  import numpy
  import pytest
  import torch
  from parameterized import parameterized
  from testing_utils import MODELS_DICT, BetterTransformersTestMixin
  from transformers import AutoModel, AutoProcessor, set_seed
  from optimum.bettertransformer import BetterTransformer
  from optimum.utils.testing_utils import grid_parameters, require_torch_gpu
label_desc: Use image node_id 4 for calling the BetterTransformersBarkTest obj's underlying member method code with example usage: obj.test_generation(test_name, model_type, batch_size) without return types